Convert model.fit_generator to model.fit

Question

I have codes in the following,

train_datagen = ImageDataGenerator(
        rescale=1./255,
        shear_range=0.2,
        zoom_range=0.2,
        horizontal_flip=True)
test_datagen = ImageDataGenerator(rescale=1./255)
train_generator = train_datagen.flow_from_directory(
        'data/train',
        target_size=(150, 150),
        batch_size=32,
        class_mode='binary')
validation_generator = test_datagen.flow_from_directory(
        'data/validation',
        target_size=(150, 150),
        batch_size=32,
        class_mode='binary')

Now model.fit_generator is defined as following:

model.fit_generator(
        train_generator,
        steps_per_epoch=2000,
        epochs=50,
        validation_data=validation_generator,
        validation_steps=800)

Now model.fit_generator is deprecated, what is the proper way to change model.fit_generator to model.fit in this case?

Answer 1

You just have to change model.fit_generator() to model.fit().

As of TensorFlow 2.1, model.fit() also accepts generators as input. As simple as that.

From TensorFlow's official documentation:

Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Please use Model.fit, which supports generators.

Answer 2

Get rid of 'generator='.

Old training:

model.fit_generator(generator=train_generator,
    steps_per_epoch=2048//36, epochs=10,
    validation_data=validation_generator, validation_steps=832//16)

New training:

model.fit(train_generator,
    steps_per_epoch=2048 // 128, epochs=10,
    validation_data=validation_generator, validation_steps=832//16)